1. Field of the Invention
The present invention relates to computer systems and methods in which data resources are shared among concurrent data consumers while preserving data integrity and consistency relative to each consumer. More particularly, the invention concerns an implementation of a mutual exclusion mechanism known as “read-copy update” in a non-preemptive real-time computing environment with processors capable of assuming low-power states.
2. Description of the Prior Art
By way of background, read-copy update is a mutual exclusion technique that permits shared data to be accessed for reading without the use of locks, writes to shared memory, memory barriers, atomic instructions, or other computationally expensive synchronization mechanisms, while still permitting the data to be updated (modify, delete, insert, etc.) concurrently. The technique is well suited to multiprocessor computing environments in which the number of read operations (readers) accessing a shared data set is large in comparison to the number of update operations (updaters), and wherein the overhead cost of employing other mutual exclusion techniques (such as locks) for each read operation would be high. By way of example, a network routing table that is updated at most once every few minutes but searched many thousands of times per second is a case where read-side lock acquisition would be quite burdensome.
The read-copy update technique implements data updates in two phases. In the first (initial update) phase, the actual data update is carried out in a manner that temporarily preserves two views of the data being updated. One view is the old (pre-update) data state that is maintained for the benefit of read operations that may have been referencing the data concurrently with the update. The other view is the new (post-update) data state that is available for the benefit of operations that access the data following the update. These other read operations will never see the stale data and so the updater does not need to be concerned with them. However, the updater does need to avoid prematurely removing the stale data being referenced by the first group of read operations. Thus, in the second (deferred update) phase, the old data state is only removed following a “grace period” that is long enough to ensure that the first group of read operations will no longer maintain references to the pre-update data. The second-phase update operation typically comprises freeing a stale data element. In certain RCU implementations, the second-phase update operation may comprise something else, such as changing an operational state according to the first-phase update.
FIGS. 1A-1D illustrate the use of read-copy update to modify a data element B in a group of data elements A, B and C. The data elements A, B, and C are arranged in a singly-linked list that is traversed in acyclic fashion, with each element containing a pointer to a next element in the list (or a NULL pointer for the last element) in addition to storing some item of data. A global pointer (not shown) is assumed to point to data element A, the first member of the list. Persons skilled in the art will appreciate that the data elements A, B and C can be implemented using any of a variety of conventional programming constructs, including but not limited to, data structures defined by C-language “struct” variables.
It is assumed that the data element list of FIGS. 1A-1D is traversed (without locking) by multiple concurrent readers and occasionally updated by updaters that delete, insert or modify data elements in the list. In FIG. 1A, the data element B is being referenced by a reader r1, as shown by the vertical arrow below the data element. In FIG. 1B, an updater u1 wishes to update the linked list by modifying data element B. Instead of simply updating this data element without regard to the fact that r1 is referencing it (which might crash r1), u1 preserves B while generating an updated version thereof (shown in FIG. 1C as data element B′) and inserting it into the linked list. This is done by u1 acquiring an appropriate lock, allocating new memory for B′, copying the contents of B to B′, modifying B′ as needed, updating the pointer from A to B so that it points to B′, and releasing the lock. As an alternative to locking, other techniques such as non-blocking synchronization or a designated update thread could be used to serialize data updates. All subsequent (post update) readers that traverse the linked list, such as the reader r2, will see the effect of the update operation by encountering B′. On the other hand, the old reader r1 will be unaffected because the original version of B and its pointer to C are retained. Although r1 will now be reading stale data, there are many cases where this can be tolerated, such as when data elements track the state of components external to the computer system (e.g., network connectivity) and must tolerate old data because of communication delays.
At some subsequent time following the update, r1 will have continued its traversal of the linked list and moved its reference off of B. In addition, there will be a time at which no other reader process is entitled to access B. It is at this point, representing expiration of the grace period referred to above, that u1 can free B, as shown in FIG. 1D.
FIGS. 2A-2C illustrate the use of read-copy update to delete a data element B in a singly-linked list of data elements A, B and C. As shown in FIG. 2A, a reader r1 is assumed be currently referencing B and an updater u1 wishes to delete B. As shown in FIG. 2B, the updater u1 updates the pointer from A to B so that A now points to C. In this way, r1 is not disturbed but a subsequent reader r2 sees the effect of the deletion. As shown in FIG. 2C, r1 will subsequently move its reference off of B, allowing B to be freed following expiration of the grace period.
In the context of the read-copy update mechanism, a grace period represents the point at which all running processes (or threads within a process) having access to a data element guarded by read-copy update have passed through a “quiescent state” in which they can no longer maintain references to the data element, assert locks thereon, or make any assumptions about data element state. By convention, for operating system kernel code paths, a context (process) switch, an idle loop, and user mode execution all represent quiescent states for any given CPU running non-preemptible code (as can other operations that will not be listed here). In some read-copy update implementations adapted for preemptible readers, all read operations that are outside of an RCU read-side critical section are quiescent states.
In FIG. 3, four processes 0, 1, 2, and 3 running on four separate CPUs are shown to pass periodically through quiescent states (represented by the double vertical bars). The grace period (shown by the dotted vertical lines) encompasses the time frame in which all four processes have passed through one quiescent state. If the four processes 0, 1, 2, and 3 were reader processes traversing the linked lists of FIGS. 1A-1D or FIGS. 2A-2C, none of these processes having reference to the old data element B prior to the grace period could maintain a reference thereto following the grace period. All post grace period searches conducted by these processes would bypass B by following the links inserted by the updater.
There are various methods that may be used to implement a deferred data update following a grace period, including but not limited to the use of callback processing as described in commonly assigned U.S. Pat. No. 5,442,758, entitled “System And Method For Achieving Reduced Overhead Mutual-Exclusion And Maintaining Coherency In A Multiprocessor System Utilizing Execution History And Thread Monitoring.” Another commonly used technique is to have updaters block (wait) until a grace period has completed.
It will be appreciated from the foregoing discussion that the fundamental operation of the read-copy update (RCU) synchronization technique entails waiting for all readers associated with a particular grace period to complete. Multiprocessor implementations of RCU must therefore observe or influence the actions performed by other processors. Non-preemptible variants of RCU require readers to avoid preemption and rescheduling. Orderly grace period processing may be ensured by waiting for execution on each reader's processor to pass through a quiescent state. However, the RCU implementation needs to coordinate with those processors to detect when a quiescent state has been reached. Moreover, the RCU implementation may choose to force the processors to enter quiescent states as soon as possible rather than waiting. This may occur if the RCU implementation decides that it has waited too long or that it has too many waiters.
RCU implementations used for non-preemptible readers do not currently account for processor power states. Modern processors benefit greatly from low-power states (such as, on Intel processors, the C1E halt state, or the C2 or deeper halt states). These low-power states have higher wakeup latency, so processors and operating systems do not choose to enter these states if frequently forced to wake up. Operating systems with mechanisms such as the dynamic tick framework (also called “dyntick” or “nohz”) in current versions of the Linux® kernel can avoid the need for regular timer interrupts (a frequent cause of unnecessary wakeups) and instead only wake up processors when they need to perform work, allowing for better utilization of low-power states. Thus, RCU implementations that force other processors to wake up and perform work can lead to higher power usage on processors with low-power higher-latency states. This may result in decreased battery life on battery-powered systems (such as laptops and embedded systems), higher power usage (particularly problematic for large data centers), increased heat output, and greater difficulty achieving compliance with various standards for environmentally friendly or “green” systems. Applicant has determined that it would be desirable to avoid unnecessary wakeups during RCU grace period processing.